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Related Experiment Video

Updated: Jun 17, 2026

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models.

Jianwei Fei, Yunshu Dai, Zhihua Xia

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |June 15, 2026
    PubMed
    Summary
    This summary is machine-generated.

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    This study introduces a new method for text-to-image model fingerprinting that resists collusion attacks. The technique embeds identifiers into personalized normalization modules, protecting intellectual property rights and preventing unauthorized redistribution.

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Model fingerprinting embeds identifiers into generative model outputs to protect intellectual property rights (IPR).
    • Existing fingerprinting methods for text-to-image (T2I) models are vulnerable to collusion attacks, where multiple attackers combine models to remove fingerprints.

    Purpose of the Study:

    • To develop a robust fingerprinting method for T2I models with anti-collusion capabilities.
    • To address the vulnerability of current fingerprinting techniques against coordinated attacks.

    Main Methods:

    • Proposed a novel method encoding fingerprints into the coefficients of a personalized normalization module (PNM) within T2I models.
    • Introduced an anti-collusion mechanism using lossless function-invariant parameter transformations to degrade colluded model quality.

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    Published on: September 26, 2016

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer
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    Published on: October 15, 2015

    Related Experiment Videos

    Last Updated: Jun 17, 2026

    Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
    12:15

    Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

    Published on: April 9, 2019

    Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
    06:55

    Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

    Published on: September 26, 2016

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer
    07:54

    Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

    Published on: October 15, 2015

  • Implemented a worst-case optimization strategy for enhanced robustness against model-level attacks.

    • Main Results:

    • Achieved high fidelity and robustness in T2I generation and editing tasks, with fingerprint extraction accuracy exceeding 99.5%.
    • Demonstrated proactive robustness against collusion attacks by significantly increasing the Fréchet Inception Distance (FID) of colluded models.
    • Enabled efficient creation of multiple fingerprinted model copies via PNM reparameterization without retraining.

    Conclusions:

    • The proposed fingerprinting method offers a robust solution against collusion attacks for T2I models.
    • The technique effectively protects intellectual property while maintaining high image generation quality.
    • This work represents a significant advancement in securing generative AI models against unauthorized use and redistribution.